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nstarman/allow-units.ipynb

Created May 2, 2021 20:09
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allow-units.ipynb
{
"cells": [
{
"cell_type": "markdown",
"id": "employed-vehicle",
"metadata": {},
"source": [
"<br><br>\n",
"\n",
"- - - \n",
"\n",
"## Prepare\n"
]
},
{
"cell_type": "markdown",
"id": "stuck-copying",
"metadata": {
"inputHidden": false,
"outputHidden": false
},
"source": [
"### Imports"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "geological-patrick",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/Users/nathanielstarkman/local/galpy/galpy/util/bovy_conversion.py:6: FutureWarning: galpy.util.bovy_conversion is being deprecated in favor of galpy.util.conversion; all functions in there are the same; please switch to the new import, because the old import will be removed in v1.9\n",
" warnings.warn('galpy.util.bovy_conversion is being deprecated in favor of galpy.util.conversion; all functions in there are the same; please switch to the new import, because the old import will be removed in v1.9',FutureWarning)\n",
"\n",
"/Users/nathanielstarkman/local/galpy/galpy/util/bovy_coords.py:6: FutureWarning: galpy.util.bovy_coords is being deprecated in favor of galpy.util.coords; all functions in there are the same; please switch to the new import, because the old import will be removed in v1.9\n",
" warnings.warn('galpy.util.bovy_coords is being deprecated in favor of galpy.util.coords; all functions in there are the same; please switch to the new import, because the old import will be removed in v1.9',FutureWarning)\n",
"\n"
]
}
],
"source": [
"# THIRD PARTY\n",
"import astropy.units as u\n",
"import astropy.coordinates as coord\n",
"from astropy.table import QTable\n",
"from astropy.tests.helper import catch_warnings\n",
"from astropy.utils.misc import NumpyRNGContext\n",
"\n",
"from galpy import potential\n",
"from galpy.orbit import Orbit\n",
"from galpy.df import streamdf\n",
"from galpy.actionAngle import actionAngleIsochroneApprox\n",
"from galpy.util import conversion\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import numpy as np\n",
"\n",
"import streamtools\n",
"from streamtools.df import streamspraydf"
]
},
{
"cell_type": "markdown",
"id": "affected-printing",
"metadata": {},
"source": [
"Setting up an orbit and potential"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "decent-destiny",
"metadata": {
"collapsed": false,
"inputHidden": false,
"jupyter": {
"outputs_hidden": false
},
"outputHidden": false
},
"outputs": [],
"source": [
"# potential\n",
"lp = potential.LogarithmicHaloPotential(normalize=1.,q=0.9)\n",
"lp.turn_physical_on()\n",
"\n",
"# progenitor properties\n",
"o = Orbit(coord.SkyCoord(coord.ICRS(\n",
" ra=229.022 * u.deg, dec=-0.112 * u.deg, distance=23.2 * u.kpc,\n",
" pm_ra_cosdec=-2.736 * u.mas / u.yr, pm_dec=-2.646 * u.mas / u.yr, radial_velocity=-58.60 * u.km / u.s,)))\n",
"\n",
"mass = 2*10.**4.*u.Msun\n",
"tdisrupt = 5*u.Gyr"
]
},
{
"cell_type": "markdown",
"id": "exceptional-passenger",
"metadata": {},
"source": [
"<br><br>\n",
"\n",
"- - - \n",
"\n",
"## With Units"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "confident-vacuum",
"metadata": {},
"outputs": [],
"source": [
"# leading\n",
"spdf_l = streamspraydf(\n",
" progenitor_mass=mass,\n",
" progenitor=o,\n",
" pot=lp,\n",
" tdisrupt=tdisrupt,\n",
" leading=True,\n",
" ro=8*u.kpc, vo=220*u.km/u.s,\n",
")\n",
"\n",
"# trailing\n",
"spdf_t = streamspraydf(\n",
" progenitor_mass=mass,\n",
" progenitor=o,\n",
" pot=lp,\n",
" tdisrupt=tdisrupt,\n",
" leading=False,\n",
" ro=8*u.kpc, vo=220*u.km/u.s,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "massive-brooklyn",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 3.07 s, sys: 35.7 ms, total: 3.11 s\n",
"Wall time: 3.17 s\n"
]
}
],
"source": [
"%%time\n",
"with NumpyRNGContext(4):\n",
"\n",
" RvR_l, dt = spdf_l.sample(n=300, returndt=True, integrate=True)\n",
" RvR_t, dt = spdf_t.sample(n=300, returndt=True, integrate=True)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "nearby-wisdom",
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$[10.058216,~7.7699016,~8.2472834,~\\dots,~7.903767,~7.7573701,~8.1571772] \\; \\mathrm{kpc}$"
],
"text/plain": [
"<Quantity [10.05821571, 7.76990165, 8.24728344, 8.23608889, 8.26252376,\n",
" 7.82733284, 7.8227129 , 8.14844061, 7.74947341, 7.7378447 ,\n",
" 9.20494365, 7.77693193, 8.71895659, 7.772061 , 7.83052182,\n",
" 8.24765065, 8.13871235, 7.71145364, 7.95918784, 8.98432985,\n",
" 7.75250956, 8.79465749, 8.91524536, 9.15514276, 7.92866238,\n",
" 7.98460295, 7.90484663, 7.86939359, 8.70831761, 7.71844585,\n",
" 7.96288743, 7.88934062, 7.77759182, 7.77703826, 7.8173244 ,\n",
" 7.7678472 , 7.92641618, 8.20699556, 7.72013942, 8.8541468 ,\n",
" 7.73502358, 7.82482812, 7.81099252, 7.68782249, 7.8188413 ,\n",
" 7.75087997, 8.57462689, 7.71318035, 7.99866913, 8.08934693,\n",
" 10.62808427, 8.21794309, 7.79804249, 7.81987087, 8.07497761,\n",
" 7.77956484, 7.86859957, 7.72347883, 8.64024617, 7.73050265,\n",
" 8.05842208, 7.75169419, 7.8378724 , 8.04175157, 8.57496489,\n",
" 7.71351094, 7.805019 , 7.97664236, 7.71909337, 7.94968243,\n",
" 7.78900347, 8.98102181, 7.92310261, 7.77921562, 8.10962382,\n",
" 8.33374308, 7.8488487 , 7.99263278, 7.80321479, 9.18051979,\n",
" 8.25294539, 7.89050409, 7.8274379 , 7.96239181, 7.73979467,\n",
" 7.98220892, 7.80509019, 8.16017687, 8.13172512, 9.19922895,\n",
" 8.12057006, 7.77217225, 7.80189225, 8.36771952, 7.74842218,\n",
" 7.8678845 , 7.98780188, 7.70090985, 8.1907516 , 7.74905378,\n",
" 7.77533147, 7.86733 , 7.85675183, 8.87862717, 9.36638765,\n",
" 7.79271711, 7.95326751, 8.11083273, 7.67460999, 7.98971968,\n",
" 7.69945491, 7.95808178, 8.00920142, 7.88545771, 8.80216123,\n",
" 8.57015222, 7.71800452, 9.4623962 , 7.73461608, 8.56116253,\n",
" 7.71880245, 9.28340154, 8.87955142, 7.89726908, 8.93172953,\n",
" 7.95698925, 8.10653457, 7.82646923, 8.02018996, 8.83771146,\n",
" 7.96360739, 7.69330104, 7.82276113, 7.78795578, 7.91904994,\n",
" 8.02052373, 8.13406738, 7.97569659, 7.92828875, 7.7911819 ,\n",
" 7.71685242, 8.35725192, 7.74341305, 8.34126493, 8.41549077,\n",
" 8.62798329, 7.78256108, 7.71948614, 8.29126911, 12.46972439,\n",
" 7.92607971, 7.81414442, 8.53870644, 10.69085747, 7.98081183,\n",
" 8.09541586, 8.07553749, 8.1103042 , 7.71564792, 7.77838497,\n",
" 7.73243522, 8.80727361, 7.73367515, 7.75612301, 7.86601032,\n",
" 8.5020847 , 9.86558514, 8.88675202, 7.98129336, 7.97697686,\n",
" 7.74320279, 11.19425429, 9.27062113, 8.6092653 , 7.87048299,\n",
" 7.95283166, 7.80107219, 7.7884748 , 7.68439351, 7.72539591,\n",
" 7.873075 , 7.705681 , 8.05698434, 7.77185927, 7.89013089,\n",
" 8.10407746, 8.10089159, 7.90698804, 8.35008248, 10.02980644,\n",
" 9.2154808 , 7.70863482, 7.84714214, 7.72404181, 7.76655187,\n",
" 8.36159424, 7.71589741, 8.4455664 , 8.8669957 , 7.79351539,\n",
" 7.78724779, 8.02946628, 8.37141382, 7.75160467, 8.00642294,\n",
" 7.75547102, 7.8838222 , 7.73543166, 7.8308416 , 7.76803922,\n",
" 7.76786479, 7.84222658, 8.60544368, 7.7191551 , 9.15550085,\n",
" 7.96570259, 7.96231404, 7.89832045, 8.93539369, 7.82187155,\n",
" 8.05134281, 8.03001108, 9.68508337, 8.11994612, 7.65982398,\n",
" 7.71246492, 7.69751696, 7.8915111 , 7.79075908, 7.73555136,\n",
" 7.71123818, 8.79994065, 7.72763513, 7.81218432, 7.87321608,\n",
" 7.80100719, 7.85237886, 7.89171276, 7.94466275, 7.78404047,\n",
" 7.72754988, 8.12244814, 8.97688797, 7.82000931, 8.02316653,\n",
" 7.84921165, 10.23583725, 7.94873997, 7.80953535, 10.15701122,\n",
" 8.03372876, 8.10918264, 7.89939039, 7.71064242, 7.72721278,\n",
" 7.73909729, 7.77661308, 8.01794196, 7.99294092, 7.98411857,\n",
" 7.80324562, 7.86754849, 7.7543682 , 8.09030138, 7.77120248,\n",
" 7.74660259, 8.50774656, 7.7691352 , 7.81197869, 8.27920685,\n",
" 7.92467086, 7.72201697, 8.074955 , 8.07506459, 7.7031963 ,\n",
" 7.70127592, 7.76243115, 7.93622314, 7.96381544, 8.86641513,\n",
" 7.7848882 , 7.89993581, 7.99258314, 7.72346123, 7.73380497,\n",
" 7.94660147, 7.80906088, 8.17126069, 7.837105 , 9.76172289,\n",
" 9.50876353, 7.74841309, 7.82318968, 8.14460514, 7.81126302,\n",
" 7.71667894, 7.93550828, 7.90376697, 7.7573701 , 8.15717719] kpc>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"RvR_l[0]"
]
},
{
"cell_type": "markdown",
"id": "addressed-wright",
"metadata": {},
"source": [
"<br><br>\n",
"\n",
"- - - \n",
"\n",
"## Without Units"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "english-screw",
"metadata": {},
"outputs": [],
"source": [
"# leading\n",
"spdf_l = streamspraydf(\n",
" progenitor_mass=mass,\n",
" progenitor=o,\n",
" pot=lp,\n",
" tdisrupt=tdisrupt,\n",
" leading=True,\n",
"# ro=8*u.kpc, vo=220*u.km/u.s,\n",
")\n",
"\n",
"# trailing\n",
"spdf_t = streamspraydf(\n",
" progenitor_mass=mass,\n",
" progenitor=o,\n",
" pot=lp,\n",
" tdisrupt=tdisrupt,\n",
" leading=False,\n",
"# ro=8*u.kpc, vo=220*u.km/u.s,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "polar-irrigation",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 3.44 s, sys: 36 ms, total: 3.47 s\n",
"Wall time: 3.53 s\n"
]
}
],
"source": [
"%%time\n",
"with NumpyRNGContext(4):\n",
"\n",
" RvR_l2, dt2 = spdf_l.sample(n=300, returndt=True, integrate=True)\n",
" RvR_t2, dt2 = spdf_t.sample(n=300, returndt=True, integrate=True)"
]
},
{
"cell_type": "markdown",
"id": "cellular-redhead",
"metadata": {},
"source": [
"- - -\n",
"Compare"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "square-denver",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"all good\n"
]
}
],
"source": [
"assert np.allclose(RvR_l[0].value, RvR_l2[0] * spdf_l._ro)\n",
"assert np.allclose(RvR_l[1].value, RvR_l2[1] * spdf_l._vo)\n",
"assert np.allclose(RvR_l[2].value, RvR_l2[2] * spdf_l._vo)\n",
"assert np.allclose(RvR_l[3].value, RvR_l2[3] * spdf_l._ro)\n",
"assert np.allclose(RvR_l[4].value, RvR_l2[4] * spdf_l._vo)\n",
"assert np.allclose(RvR_l[5].value, RvR_l2[5])\n",
"\n",
"print(\"all good\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "earlier-immigration",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "dev",
"language": "python",
"name": "dev"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.2"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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